
On the Iteration Complexity of Hypergradient Computation
We study a general class of bilevel problems, consisting in the minimiza...
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Scheduling the Learning Rate via Hypergradients: New Insights and a New Algorithm
We study the problem of fitting taskspecific learning rate schedules fr...
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Learning Discrete Structures for Graph Neural Networks
Graph neural networks (GNNs) are a popular class of machine learning mod...
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Fast and Continuous Foothold Adaptation for Dynamic Locomotion through Convolutional Neural Networks
Legged robots can outperform wheeled machines for most navigation tasks ...
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FarHO: A Bilevel Programming Package for Hyperparameter Optimization and MetaLearning
In (Franceschi et al., 2018) we proposed a unified mathematical framewor...
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Bilevel Programming for Hyperparameter Optimization and MetaLearning
We introduce a framework based on bilevel programming that unifies gradi...
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A Bridge Between Hyperparameter Optimization and Larningtolearn
We consider a class of a nested optimization problems involving inner an...
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Forward and Reverse GradientBased Hyperparameter Optimization
We study two procedures (reversemode and forwardmode) for computing th...
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Luca Franceschi
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